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Tumor antigens and immune subtypes of glioblastoma: the fundamentals of mRNA vaccine and individualized immunotherapy development.
Wu, Changwu; Qin, Chaoying; Long, Wenyong; Wang, Xiangyu; Xiao, Kai; Liu, Qing.
Afiliação
  • Wu C; Department of Neurosurgery, Xiangya Hospital, Central-South University, 87 Xiangya Road, Changsha, 410008 Hunan People's Republic of China.
  • Qin C; Department of Neurosurgery, Xiangya Hospital, Central-South University, 87 Xiangya Road, Changsha, 410008 Hunan People's Republic of China.
  • Long W; Department of Neurosurgery, Xiangya Hospital, Central-South University, 87 Xiangya Road, Changsha, 410008 Hunan People's Republic of China.
  • Wang X; Department of Neurosurgery, Xiangya Hospital, Central-South University, 87 Xiangya Road, Changsha, 410008 Hunan People's Republic of China.
  • Xiao K; Department of Neurosurgery, Xiangya Hospital, Central-South University, 87 Xiangya Road, Changsha, 410008 Hunan People's Republic of China.
  • Liu Q; Department of Neurosurgery, Xiangya Hospital, Central-South University, 87 Xiangya Road, Changsha, 410008 Hunan People's Republic of China.
J Big Data ; 9(1): 92, 2022.
Article em En | MEDLINE | ID: mdl-35855914
Purpose: Glioblastoma (GBM) is the most common primary brain tumor in adults and is notorious for its lethality. Given its limited therapeutic measures and high heterogeneity, the development of new individualized therapies is important. mRNA vaccines have exhibited promising performance in a variety of solid tumors, those designed for glioblastoma (GBM) need further development. The aim of this study is to explore tumor antigens for the development of mRNA vaccines against GBM and to identify potential immune subtypes of GBM to identify the patients suitable for different immunotherapies. Methods: RNA-seq data and the clinical information of 143 GBM patients was extracted from the TCGA database; microarray data and the clinical information of 181 GBM patients was obtained from the REMBRANDT cohort. A GBM immunotherapy cohort of 17 patients was obtained from a previous literature. GEPIA2, cBioPortal, and TIMER2 were used to identify the potential tumor antigens. Immune subtypes and gene modules were identified using consensus clustering; immune landscape was constructed using graph-learning-based dimensionality reduction analysis. Results: Nine potential tumor antigens associated with poor prognosis and infiltration of antigen-presenting cells were identified in GBM: ADAMTSL4, COL6A1, CTSL, CYTH4, EGFLAM, LILRB2, MPZL2, SAA2, and LSP1. Four robust immune subtypes and seven functional gene modules were identified and validated in an independent cohort. Immune subtypes had different cellular and molecular characteristics, with IS1, an immune cold phenotype; IS2, an immune hot and immunosuppressive phenotype; IS3, a relatively immune cold phenotype, second only to IS1; IS4, having a moderate tumor immune microenvironment. Immune landscape revealed the immune distribution of the GBM patients. Additionally, the potential value of immune subtypes for individualized immunotherapy was demonstrated in a GBM immunotherapy cohort. Conclusions: ADAMTSL4, COL6A1, CTSL, CYTH4, EGFLAM, LILRB2, MPZL2, SAA2, and LSP1 are the candidate tumor antigens for mRNA vaccine development in GBM, and IS1 GBM patients are best suited for mRNA vaccination, IS2 patients are best suited for immune checkpoint inhibitor. This study provides a theoretical framework for GBM mRNA vaccine development and individualized immunotherapy strategies. Supplementary Information: The online version contains supplementary material available at 10.1186/s40537-022-00643-x.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: J Big Data Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: J Big Data Ano de publicação: 2022 Tipo de documento: Article